Datadog + PagerDuty
Datadog + PagerDuty: Automate Incident Response from Alert to Resolution
Connect your monitoring and on-call management platforms to cut manual triage and get to resolution faster.
Why integrate Datadog and PagerDuty?
Datadog and PagerDuty are the backbone of modern incident management. Datadog surfaces anomalies, performance degradations, and infrastructure failures; PagerDuty makes sure the right engineers are notified and moving. Together, they form a closed-loop alerting and response system that keeps services up and teams focused. Integrating them through tray.ai lets you automate the entire path from a triggered Datadog monitor to a resolved PagerDuty incident, with full control over routing logic, escalation policies, and enrichment.
Automate & integrate Datadog & PagerDuty
Use case
Automated Incident Creation from Datadog Monitor Alerts
When a Datadog monitor transitions to an ALERT state, tray.ai opens a new PagerDuty incident with full monitor metadata — metric values, tags, dashboard links, and host information. This cuts the lag between detection and notification, so on-call engineers have all the context they need before they even pick up the phone.
Use case
Intelligent Alert Routing Based on Service and Team Tags
Use Datadog monitor tags like `team:payments` or `service:checkout-api` to dynamically route PagerDuty incidents to the correct escalation policy and on-call schedule. tray.ai reads tag metadata at trigger time and maps it to the right PagerDuty service, so alerts don't land in the wrong queue.
Use case
Auto-Resolve PagerDuty Incidents When Datadog Monitors Recover
When a Datadog monitor returns to OK, tray.ai automatically resolves the matching PagerDuty incident so stale open incidents don't pile up and drain attention. The workflow includes a reconciliation step that matches the originating Datadog event to the right PagerDuty incident before closing it.
Use case
Maintenance Window Suppression and Alert Muting
When a scheduled Datadog downtime is created, tray.ai can automatically place the corresponding PagerDuty service into maintenance mode, blocking unnecessary pages during planned infrastructure changes. Once the window closes in Datadog, PagerDuty services come back online automatically.
Use case
Incident Enrichment with Datadog Metric Snapshots
When a PagerDuty incident is created, tray.ai queries the Datadog API for a live metric snapshot or dashboard screenshot and attaches it directly to the incident as a note. On-call engineers see the relevant graph immediately, without logging into Datadog separately.
Use case
Post-Incident Reporting and Metrics Aggregation
After a PagerDuty incident resolves, tray.ai pulls the incident timeline — acknowledgment time, resolution time, responder activity — and correlates it with the originating Datadog event to produce a structured post-mortem record. That data can go to a data warehouse, Confluence, or a Jira ticket for review.
Use case
Escalation Policy Synchronization Triggered by Metric Severity
tray.ai evaluates the severity of a Datadog alert — based on metric thresholds, anomaly scores, or custom tags — and dynamically assigns the right PagerDuty urgency level and escalation policy. Critical infrastructure alerts go to senior engineers; low-severity warnings follow a lower-urgency path.
Get started with Datadog & PagerDuty integration today
Datadog & PagerDuty Challenges
What challenges are there when working with Datadog & PagerDuty and how will using Tray.ai help?
Challenge
Mapping Datadog Monitor Tags to PagerDuty Services at Scale
In large environments with hundreds of Datadog monitors and dozens of PagerDuty services, manually maintaining a mapping between alert tags and the correct on-call service is error-prone and expensive to operate. Mismatches mean alerts go to the wrong team, or nobody gets paged at all.
How Tray.ai Can Help:
tray.ai gives you a codeless mapping layer where you define and update tag-to-service routing rules without touching individual monitors or PagerDuty configurations. Rules live in tray.ai data tables and update centrally, so team reorganizations and new service onboarding don't require a configuration audit across every monitor you own.
Challenge
Avoiding Duplicate Incidents from Repeated Datadog Flaps
Datadog monitors can flap between ALERT and OK states in quick succession, especially during intermittent network issues or noisy thresholds. Without deduplication logic, each flap generates a new PagerDuty incident, flooding on-call queues and wearing out responders.
How Tray.ai Can Help:
tray.ai workflows implement deduplication logic using Datadog monitor IDs and a configurable suppression window. Before creating a new PagerDuty incident, tray.ai checks whether an open incident for the same monitor already exists, blocking duplicate pages during flapping conditions.
Challenge
Keeping Incident State in Sync Across Both Platforms
When an incident is acknowledged or resolved in PagerDuty, that state change doesn't automatically appear in Datadog, and vice versa. The two systems end up telling different stories about the same event, which creates confusion in dashboards, runbooks, and post-incident reviews.
How Tray.ai Can Help:
tray.ai runs bidirectional sync workflows that listen for state change webhooks on both platforms and propagate updates in real time. A PagerDuty acknowledgment annotates the Datadog event stream; a Datadog recovery triggers a PagerDuty resolution. Both systems stay consistent.
Challenge
Handling Authentication and API Rate Limits Reliably
Incident response is time-critical, and API authentication failures or rate limit errors at the wrong moment can delay incident creation when it matters most. Both Datadog and PagerDuty enforce rate limits that need careful management in high-alert-volume environments.
How Tray.ai Can Help:
tray.ai manages API credentials through its built-in secrets vault and handles rate limit responses with automatic retry and backoff logic. Workflows are monitored in real time, with error alerting and dead-letter queuing so no alert gets silently dropped, even under heavy load.
Challenge
Enriching Sparse Alerts with Actionable Context
Datadog webhooks often deliver minimal data — a monitor name and a metric value — leaving on-call engineers without enough context to diagnose quickly. Pulling additional information manually from dashboards, logs, and service catalogs adds precious minutes to response time.
How Tray.ai Can Help:
tray.ai workflows automatically query the Datadog API for additional context — related logs, metric snapshots, infrastructure maps, and service dependencies — and embed that data directly into the PagerDuty incident description and notes before the first page goes out.
Start using our pre-built Datadog & PagerDuty templates today
Start from scratch or use one of our pre-built Datadog & PagerDuty templates to quickly solve your most common use cases.
Datadog & PagerDuty Templates
Find pre-built Datadog & PagerDuty solutions for common use cases
Template
Datadog Monitor Alert → PagerDuty Incident Auto-Create
Listens for ALERT state changes on any Datadog monitor and automatically creates a new PagerDuty incident with full monitor context, tags, metric values, and a direct link back to the Datadog event.
Steps:
- Trigger: Datadog webhook fires when a monitor enters ALERT state
- Transform: tray.ai maps monitor name, tags, metric data, and runbook URL to PagerDuty incident fields
- Action: PagerDuty incident is created and routed to the appropriate service and escalation policy
Connectors Used: Datadog, PagerDuty
Template
Datadog Monitor Recovery → PagerDuty Incident Auto-Resolve
Watches Datadog for OK state transitions and automatically resolves the matching PagerDuty incident, keeping on-call queues clean and MTTR metrics accurate.
Steps:
- Trigger: Datadog webhook fires when a monitor recovers to OK state
- Lookup: tray.ai queries PagerDuty to find the open incident matching the Datadog monitor ID
- Action: PagerDuty incident is resolved and a resolution note is appended with Datadog recovery details
Connectors Used: Datadog, PagerDuty
Template
Datadog Maintenance Window → PagerDuty Service Maintenance Sync
Automatically places PagerDuty services into maintenance mode when a Datadog scheduled downtime is created, and re-enables them when the downtime ends.
Steps:
- Trigger: Datadog scheduled downtime creation event detected via API poll or webhook
- Map: tray.ai identifies affected hosts or services and finds corresponding PagerDuty services
- Action: PagerDuty maintenance window is created for the same duration; a follow-up step disables it on expiry
Connectors Used: Datadog, PagerDuty
Template
PagerDuty Incident Acknowledged → Datadog Event Timeline Annotation
When an on-call engineer acknowledges a PagerDuty incident, tray.ai posts a corresponding annotation to the Datadog event timeline, giving full visibility into response activity directly inside your monitoring dashboard.
Steps:
- Trigger: PagerDuty webhook fires on incident acknowledgment event
- Extract: tray.ai retrieves acknowledging user, timestamp, and incident details from PagerDuty
- Action: A Datadog event is posted to the timeline with responder name, acknowledgment time, and incident link
Connectors Used: PagerDuty, Datadog
Template
Severity-Based Datadog Alert → Dynamic PagerDuty Escalation Routing
Reads the severity tag or metric threshold on incoming Datadog alerts and routes them to different PagerDuty services, urgency levels, and escalation policies based on configurable business rules.
Steps:
- Trigger: Datadog alert received with severity tag (e.g., P1, P2, warning)
- Branch: tray.ai applies conditional logic to determine the target PagerDuty service and urgency level
- Action: PagerDuty incident is created with the correct urgency, escalation policy, and assigned team
Connectors Used: Datadog, PagerDuty
Template
Resolved PagerDuty Incident → Post-Mortem Record Creation
After a PagerDuty incident resolves, tray.ai compiles the incident timeline, correlates it with Datadog monitor history, and creates a structured post-mortem entry in Confluence, Jira, or a connected data store.
Steps:
- Trigger: PagerDuty incident moves to resolved status
- Enrich: tray.ai fetches incident timeline, MTTA/MTTR metrics, and correlated Datadog monitor history
- Action: Structured post-mortem record is created in the configured destination with all incident data
Connectors Used: PagerDuty, Datadog